Fine-Tune and Integrate Custom Phi-3 Models with Prompt Flow in Azure AI Studio
Phi-3 is a family of small language models (SLMs) developed by Microsoft that delivers exceptional performance and cost-effectiveness. In this tutorial, you will learn how to fine-tune the Phi-3 model and integrate the custom Phi-3 model with Prompt flow in Azure AI Studio. By leveraging Azure AI / ML Studio, you will establish a workflow for deploying and utilizing custom AI models.Fine-Tune and Integrate Custom Phi-3 Models with Prompt Flow: Step-by-Step Guide
In this tutorial, you will learn how to fine-tune the Phi-3 model and integrate it with Prompt Flow. By leveraging Azure Machine Learning, and Prompt flow you will establish a workflow for deploying and utilizing custom AI models.Evaluating Generative AI Models with Azure Machine Learning
LLM evaluation assesses the performance of a large language model on a set of tasks, such as text classification, sentiment analysis, question answering, and text generation. The goal is to measure the model's ability to understand and generate human-like language.Integrating Power Apps with Azure Machine Learning & OpenAI using Power Automate
Learn how to integrate Power Apps with Azure Machine Learning & OpenAI using Power Automate through a Health Expense Planner Application. This app allows the user to predict their Health Expense using a Machine Learning Model and then get a detailed personalized plan to save funds for it.Your Startup's Secret Weapon for AI Success - Foundation Models in Azure Machine Learning
In the past, managing and using large models has been a cumbersome task, with customers having to manage the infrastructure and environment dependencies for these models. Foundational models, at their core, are pre-built machine learning models that have been meticulously crafted and fine-tuned by experts. These models serve as a rock-solid foundation upon which startups can build their AI applications.
